Field of the Subject Disclosure
The present subject disclosure relates to spectral unmixing in fluorescence microscopy. More particularly, the present subject disclosure relates to estimating reference spectra for predominantly broadband regions of an image and using the reference spectra to unmix desired regions of the image.
Background of the Subject Disclosure
In the analysis of biological specimens such as tissue sections, blood, cell cultures and the like, fluorescence microscopy is used to generate images of biological specimens which are stained with one or more fluorophores. Biological specimens, such as tissue sections from human subjects, can be treated with a stain containing an organic fluorophore conjugated to an antibody which binds to protein, protein fragments, or other targets in the specimen. For instance, the specimen may be stained with 4′,6-diamidino-2-phenylindole (DAPI). The stained specimen is then illuminated with light and the stain fluoresces. A digital camera attached to a microscope is then used to capture an image of the specimen. The areas where the fluorophore/antibody combination became bound to the target of interest (e.g., proliferation protein produced by cancerous cells) appear as colored regions in the image of the specimen, with the color of the area dictated by the fluorescence spectrum of the fluorophore applied to the specimen. In addition to the visible spectrum, the fluorescence signal may be detected in the infra-red or ultra-violet regions, depending on emission spectrum of the particular fluorophore. A stain containing two or more fluorophores can also be applied to the specimen. These methods have a variety of uses, including diagnosis of disease, assessment of response to treatment, and development of new drugs to fight disease. Recently increased use of nano-crystalline luminescent semiconductor materials known as “quantum dots” as a stain material for biological staining and imaging applications poses several advantages over traditional organic fluorophores. These advantages include narrow emission band peaks, broad absorption spectra, intense signals, and strong resistance to bleaching or other degradation.
An observed signal is typically a mixture of multiple signals that are linearly mixed. The problem of unmixing them, i.e. going back to the original components from the observed signal, is solved by spectral unmixing the resulting image or portions thereof. This is a standard linear algebra problem that is properly applied to positive (or non-negative) signals, such as those emitted by fluorophores. Thus, a non-negative linear least squares method is typically used. For instance, in medical imaging, each location may include 16 signals, where the goal would be to isolate between 6-10 desired signals, or signals that are known to correspond to a quantum dot or other target signal. However, there is a mixture of signals at each point or pixel in the image. Therefore, for a 10,000×10,000 image with 16 channels, the unmixing process would be resource-intensive and cumbersome. Traditionally, one would unmix at each location or pixel using a linear equation solver. However, a complication arises when autofluorescence and DAPI are in the spectrum of detected signals. These are broadband signals, noisy, and hide the quantum dots. Autofluorescence and DAPI change from image to image, and from location to location, and this results in intensive computation and unclear results. This is further complicated by variety in sample types, such as tissues from various organs and organisms. Even known broadband signatures, when applied universally to specific samples, rest on an assumption that these reference spectra are fixed throughout the image, and thereby lead to imperfect results. DAPI, for instance, is only useful for staining nuclei and getting a context of the image. Also, DAPI is a broadband signal, that overwhelms other signals, and occurs in large regions. The same applies to red blood cells (RBCs) and lipofuscin, which respectively have highly broadband signals (RBC), and autofluorescence (lipofuscin). These signals are largely unnecessary from a diagnostic perspective, and it is desired that they are removed.